The article discusses the urgent need for validated tests of consciousness (C-tests) applicable to a wide range of systems, including humans, non-human animals, AI, and neural organoids. It highlights the challenges in developing such tests and proposes a multidimensional framework for classifying and validating them. The authors identify key dimensions of C-tests, such as target population, specificity, sensitivity, and rational confidence, and suggest a strategy that starts with non-trivial human cases (e.g., infants, disorders of consciousness) and progresses to non-human systems. They emphasize the importance of C-tests in understanding the distribution of consciousness and evaluating theories of consciousness, as well as their moral implications. The article also explores various strategies for validating C-tests, including redeployment of existing tests, theory-based approaches, and an iterative natural kind (NK) strategy that builds on consensus cases. The NK strategy is presented as a promising approach, though it faces challenges related to the possibility of multiple realizations of consciousness. The review concludes that while a universal C-test may be difficult to achieve, a battery of tests tailored to different populations and aspects of consciousness is likely necessary. The article underscores the importance of addressing the philosophical and empirical challenges in defining and validating consciousness across diverse systems.The article discusses the urgent need for validated tests of consciousness (C-tests) applicable to a wide range of systems, including humans, non-human animals, AI, and neural organoids. It highlights the challenges in developing such tests and proposes a multidimensional framework for classifying and validating them. The authors identify key dimensions of C-tests, such as target population, specificity, sensitivity, and rational confidence, and suggest a strategy that starts with non-trivial human cases (e.g., infants, disorders of consciousness) and progresses to non-human systems. They emphasize the importance of C-tests in understanding the distribution of consciousness and evaluating theories of consciousness, as well as their moral implications. The article also explores various strategies for validating C-tests, including redeployment of existing tests, theory-based approaches, and an iterative natural kind (NK) strategy that builds on consensus cases. The NK strategy is presented as a promising approach, though it faces challenges related to the possibility of multiple realizations of consciousness. The review concludes that while a universal C-test may be difficult to achieve, a battery of tests tailored to different populations and aspects of consciousness is likely necessary. The article underscores the importance of addressing the philosophical and empirical challenges in defining and validating consciousness across diverse systems.